100 citations · 223 across the 14 of their papers we have counts for
16 papers
Exploring Deep Learning Image Super-Resolution for Iris Recognition
Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez +1
In this work we test the ability of deep learning methods to provide an end-to-end mapping between low and high resolution images applying it to the iris recognition problem. Here,…
Deep Learning in the Field of Biometric Template Protection: An Overview
Christian Rathgeb, Jascha Kolberg, Andreas Uhl +1
Today, deep learning represents the most popular and successful form of machine learning. Deep learning has revolutionised the field of pattern recognition, including biometric rec…
Advanced Image Quality Assessment for Hand- and Fingervein Biometrics
Simon Kirchgasser, Christof Kauba, Georg Wimmer +1
Natural Scene Statistics commonly used in non-reference image quality measures and a deep learning based quality assessment approach are proposed as biometric quality indicators fo…
Experimental analysis regarding the influence of iris segmentation on the recognition rate
Heinz Hofbauer, Fernando Alonso-Fernandez, Josef Bigun +1
In this study the authors will look at the detection and segmentation of the iris and its influence on the overall performance of the iris-biometric tool chain. The authors will ex…
Iris super-resolution using CNNs: is photo-realism important to iris recognition?
Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez
The use of low-resolution images adopting more relaxed acquisition conditions such as mobile phones and surveillance videos is becoming increasingly common in iris recognition nowa…
Super-Resolution and Image Re-projection for Iris Recognition
Eduardo Ribeiro, Andreas Uhl, Fernando Alonso-Fernandez
Several recent works have addressed the ability of deep learning to disclose rich, hierarchical and discriminative models for the most diverse purposes. Specifically in the super-r…
Extensive Threat Analysis of Vein Attack Databases and Attack Detection by Fusion of Comparison Scores
Johannes Schuiki, Michael Linortner, Georg Wimmer +1
The last decade has brought forward many great contributions regarding presentation attack detection for the domain of finger and hand vein biometrics. Among those contributions, o…
Roadmap on Signal Processing for Next Generation Measurement Systems
D. K. Iakovidis, M. Ooi, Y. C. Kuang +31
Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, image…
Using CNNs to Identify the Origin of Finger Vein Image
Babak Maser, Andreas Uhl
We study the finger vein (FV) sensor model identification task using a deep learning approach. So far, for this biometric modality, only correlation-based PRNU and texture descript…
Identifying the Origin of Finger Vein Samples Using Texture Descriptors
Babak Maser, Andreas Uhl
Identifying the origin of a sample image in biometric systems can be beneficial for data authentication in case of attacks against the system and for initiating sensor-specific pro…
Two-stage CNN-based wood log recognition
Georg Wimmer, Rudolf Schraml, Heinz Hofbauer +2
The proof of origin of logs is becoming increasingly important. In the context of Industry 4.0 and to combat illegal logging there is an increasing motivation to track each individ…
Enabling Fingerprint Presentation Attacks: Fake Fingerprint Fabrication Techniques and Recognition Performance
Christof Kauba, Luca Debiasi, Andreas Uhl
Fake fingerprint representation pose a severe threat for fingerprint based authentication systems. Despite advances in presentation attack detection technologies, which are often i…
Improving Endoscopic Decision Support Systems by Translating Between Imaging Modalities
Georg Wimmer, Michael Gadermayr, Andreas Vécsei +1
Novel imaging technologies raise many questions concerning the adaptation of computer-aided decision support systems. Classification models either need to be adapted or even newly…
Demographic Bias: A Challenge for Fingervein Recognition Systems?
P. Drozdowski, B. Prommegger, G. Wimmer +4
Recently, concerns regarding potential biases in the underlying algorithms of many automated systems (including biometrics) have been raised. In this context, a biased algorithm pr…
Deep Learning with Topological Signatures
Christoph Hofer, Roland Kwitt, Marc Niethammer +1
Inferring topological and geometrical information from data can offer an alternative perspective on machine learning problems. Methods from topological data analysis, e.g., persist…
Proceedings of The 39th Annual Workshop of the Austrian Association for Pattern Recognition (OAGM), 2015
Sebastian Hegenbart, Roland Kwitt, Andreas Uhl
The 39th annual workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR) provides a platform for presentation and discussion of research progress as well as researc…